Tinybeans achieves faster time to insights and 85% less ad hoc data requests w/ Zenlytic

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Tinybeans [ANX:TNY] is a family photo sharing app that helps parents capture and organize their children’s life stories using photos, video, and written messages. Prior to finding Zenlytic, Tinybeans was using Tableau as their visualization layer and struggling to drive data adoption across their company.


While Tableau is great for building beautiful dashboards and visualizations, Tinybeans found that it wasn’t helping their non-technical users get the data they needed, when they needed it, to make crucial business decisions.

When their dashboards fell short, Tinybeans’ endusers would email their data questions to their small, overrun data team and wait hours (or days) to hear back. On the flip side, all these ad hoc data questions bottlenecked the data team. Senior Data Analyst, Merinne, found that she was spending the majority of her time servicing ad hoc questions rather than focusing on the more advanced projects that she was uniquely qualified to solve.


Zenlytic emerged as the obvious answer to enable fast, reliable insights across Tinybeans’ entire team. By combining the power of large language models with the precision of a semantic layer.


1. Speed of Insights: With Zenlytic, Tinybeans has increased their time to insights from days to seconds. This enables business leaders to get the data they need, when they need it, to make better decisions.

2. Reduction in Ad hoc Requests: Zenlytic has decreased the frequency of ad hoc requests by 80% to 90%, freeing up more time for the data team to focus on strategic projects that really move the needle.

3. Data-driven culture: The beauty of Zenlytic is that it bridges the divide between business leaders and the data those business leaders need to do their job better.


Zenlytic utilizes the latest technological advancements in AI to enable powerful self-serve analytics. With Zenlytic, Tinybeans has built a data-driven culture that operates on insights rather than instincts.


Want to see how Zenlytic can make sense of all of your data?

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What does implementation look like?

First you connect Zenlytic to your warehouse. Then you build out your semantic layer — which involves defining your business metrics, table joins, RBAC, etc. Then you are ready to go! We have AI tooling that significantly accelerates the process of defining your metrics. It could take a couple hours to a couple weeks.

Do I need an OpenAI API key?


What do I need to set it up?

You need to have a data warehouse - we support Snowflake/BigQuery/Redshift

Do I need dbt?

You don’t need it, but dbt partners and Zenlytic works great with dbt!

How do you ensure the LLMs don’t hallucinate and give inaccurate data?

LLMs are going to change the way we consume data but they also have a tendency to make inaccurate inferences. To counter this, we use a semantic layer for precision. The LLM translates a natural language question into a format that is understood by the semantic layer, and the semantic layer generates a SQL query that returns data.

Is Zenlytic just an AI powered chatbot?

No. Zenlytic is a fully featured business intelligence tool with robust dashboards, scheduled reports, RBAC, Visual Exploration and much more!

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